Sleep apnea syndrome (SAS) is a common respiratory disorder. By definition, apnea is the cessation of airflow to the lungs (usually during sleep) which lasts for at least 10 seconds. Polysomnography (PSG) during the entire night is currently the only reliable diagnostic method of sleep apnea. The standard PSG consists of recording various physiological parameters including EEG, ECG, EMG of chins and legs, nasal airflow, electro-oculogram (EOG), abdominal and thoracic movements, and blood oxygen saturation (SaO2). However, the high cost of the system, discomfort of the electrodes connecting to the body and the high amount of information required to be analyzed are the main disadvantages of this method.
Several researchers have tried to detect apnea using smaller number of features such as airflow, SaO2 and respiratory effort. Also, in a recent study an acoustical method based on lung sounds power at different frequency ranges was proposed for apnea and snore detection with a sensitivity of about 77% at best situation. In the other studies airflow was measured using either face masks or nasal cannulae and its cessation was detected as the main sign of apnea. However, face mask results in unavoidable changes in breathing pattern and also its application is a challenge when studying children with neurological impairments. On the other hand, usage of nasal cannulae is highly questionable due to the leakage of airflow and possibility of breathing through the mouth.
Sleep apnea syndrome (SAS) can become very serious. It is most common in obese people, people with high blood pressure, people with narrowed airway due to tonsils or adenoids, people with stroke or brain injuries, and smokers. Sleep apnea occurs two to three times more often in the elderly and also more in males than in females. It can cause cardiovascular problems, daytime fatigue, irritability, lack of concentration and sleepiness causing accidents. Most people with obstructive sleep apnea snore; but not everybody that snores has sleep apnea.
Analysis of breathing sounds from a patient for determination of sleep apnea and/or hypopnea is proposed in a paper entitled “Validation of a New System of Tracheal sound Analysis for the diagnosis of Sleep Apnea-Hypopnea Syndrome” by Nakano et al in “SLEEP” Vol 27 No. 5 published in 2004. This constitutes a research paper postulating that sleep apnea can be detected by breathing sound analysis but providing no practical details for a system which may be used in practise. It is believed that no further work has been published and no commercial machine has arisen from this paper.
U.S. Pat. No. 6,290,654 (Karakasoglu) issued Sep. 18, 2001 discloses an apparatus for analyzing sounds to estimate airflow for the purposes of detecting apnea events. It then uses a pattern recognition circuitry to detect patterns indicative of an upcoming apnea event. In this patent two microphones located close to the patients face and on patient's trachea are used to record respiratory sounds and ambient noise, respectively. The third sensor records oxygen saturation. Two methods based on adaptive filter were applied to remove the ambient noise from respiratory sounds. Then the signal was band-pass filtered and used for airflow estimation. The estimated airflow signals from two sensors and oxygen saturation data were fed to a wavelet filter to extract respiratory features. Then the extracted features along with the logarithm values of the estimated airflow, signals from two sensors and oxygen saturation sensor were applied to a neural network to find normal and abnormal respiratory patterns. In the next step k-mans classifier was used to find apnea and hypopnea events in the abnormal respiratory patterns. In this patent after removing background noise from the signals, the signals are fed to a filter bank which consists of a series of filters in the range of 3001500 with bandwidth of 100 Hz and then the output of the filter with higher signal to noise ration is selected for flow estimation. Respiratory sounds data below 300 Hz are crucial for flow estimation during shallow breathing which occurs during sleep. Finally in this patent both acoustical signals and oxygen saturation data are used for apnea detection,
In U.S. Pat. No. 5.797,852 (Karakasoglu) assigned to Local Silence Inc filed 1993 and issued 1998 and now expired is disclosed an apparatus for detecting sleep apnea using a first microphone for detection of breathing sounds and a second microphone for cancelling ambient sounds. This patent apparently lead to release of a machine called “Silent Night” which was approved by FDA in 1997 but apparently is no longer available. In this patent a system comprised of two microphones is proposed for apnea detection. The first microphone is placed near the nose and mouth of the subject to record inhaling and exhaling sounds and the second microphone is positioned in the air near the patient to record ambient noise. The data of the second microphone is used to remove ambient noise from the first signal by means of adaptive filtering. Then the filtered signal is applied to a model for estimating flow and classifying as apnea or normal breathing. The way the patent proposes to record signals it is obvious that the author has never done any experiment with the respiratory sounds. In this patent the main signal is recorded from a place “near” mouth and nose. This is a very vague description of the microphone location and will not record any respiratory sounds especially at low flow rates, which is the rate during sleep usually.
A related U.S. Pat. No. 5,844,996 (Enzmann and Karakasoglu) issued 1998 to Sleep Solutions Inc is directed to reducing snoring sounds by counteracting the sounds with negative sounds. This Assignee has a sleep apnea detection system currently on sale called NovaSom QSG but this uses sensors of a conventional nature and does not attempt to analyze breathing sounds. In this patent a method for removing snoring sounds is proposed. The patent consists of two microphones and a speaker. The first microphone is placed near the noise source to record the noise. The recorded noise is analyzed to generate a signal with opposite amplitude and sign and played by the speaker to neutralize noise in the second position. In order to decrease the error, the second microphone is placed in the second position to get the overall signal and noise and compensate for the noise. This patent is about noise cancellation and specially snoring sound, not apnea detection or screening. The first microphone which provides the primary signal is placed near the head of the subject and not in a place suitable for recording respiratory sounds. Nothing is done for flow estimation or apnea detection.
U.S. Pat. No. 6,241,683 (Macklem) issued Jun. 5, 2001 discloses a method for estimating air flow from breathing sounds where the system determines times when sounds are too low to make an accurate determination and uses an interpolation method to fill in the information in these times. Such an arrangement is of course of no value in detecting apnea or hypopnea since it accepts that the information in these times is inaccurate. In this patent tracheal sound is used for estimation of flow ventilation parameters. Although they mentioned their method can be used to detect several respiratory diseases including sleep apnea, their main focus is not on the sleep apnea detection by acoustical means. They do not mention how they are going to remove ambient noise and snoring sounds from the recordings nor the use of oxygen saturation data for further investigations. Also they have used wired microphone placed over trachea. The other difference is in the signal processing method applied for flow estimation. They are using average power of tracheal sound for flow estimation but it has been shown that average power can not follow flow changes accurately. Also in this study the recorded respiratory sounds are bandpass filtered in the range of [200-1000]Hz to remove heart sounds, which results in low accuracy in estimating flow during shallow breathing.
U.S. Pat. No. 6,666,830 (Lehrman) issued Dec. 23, 2003 discloses an apparatus for analyzing sounds to detect patterns indicative of an upcoming apnea event. It does not attempt to determine an estimate of air flow to actually locate an apnea event but instead attempts to detect changes in sound caused by changes in airflow patterns through the air passages of the patient. In this patent four microphones are located on a collar around the neck to measure respiratory sounds and a sensor is placed close to nostrils to measure airflow. The airflow signal is used to find breathing pattern and the microphones signals are filtered and analyzed to find the onset of apnea event. In this patent snoring and ambient noise detection has not been discussed. This arrangement does not estimate flow from respiratory sounds so that they cannot calculate respiratory parameters such as respiratory volume based on flow data.
Polysomnography (PSG) testing during the entire night is currently the accepted gold standard diagnostic method of sleep apnea. The standard PSG consists of recording various physiological parameters including EEG, ECG, EMG of chins and legs, nasal airflow, electro-oculogram (EOG), abdominal and thoracic movements, and blood oxygen saturation (SaO2) and usually snoring sounds. However, the high cost of the system, discomfort of the electrodes connecting to the body and the high amount of information required to be analyzed are the major disadvantages of this testing method.
This complexity of the monitoring system causes a very long waiting list for patients to go through a sleep study. Hence healthcare providers and payers are seeking alternative methods, portable devices and automated/intelligent systems in which sleep apnea testing can be done at the home of patient but with the same diagnostic values.